Robust and Rapid Air-Borne Odor Tracking without Casting

Urvashi, Bhattacharyya,; Bhalla, Upinder S.

doi:10.1523/eneuro.0102-15.2015

Cited by 33 publications

(41 citation statements)

References 31 publications

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“…There is currently little information available on how terrestrial animals track airborne odors [14,31], with most information coming from studies using invertebrates [15]. Here, we used controlled laboratory conditions to demonstrate that mice can make use of airborne odor cues to locate a source.…”

Section: Discussionmentioning

confidence: 99%

Mice Develop Efficient Strategies for Foraging and Navigation Using Complex Natural Stimuli

Gire¹,

Kapoor²,

Arrighi‐Allisan³

et al. 2016

Current Biology

101

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SUMMARY The ability to shift between multiple decision-making strategies during natural behavior allows animals to strike a balance between flexibility and efficiency. We investigated odor-guided navigation by mice to understand how decision making strategies are balanced during a complex natural behavior. Mice navigated to odor sources in an open arena using naturally fluctuating airborne odor cues as their positions were recorded precisely in real time. When mice had limited prior experience of source locations, their search behavior was consistent with a gradient ascent algorithm that utilized directional cues in the plume to navigate to the odor source. Gradient climbing was effective because the arena size allowed animals to conduct their search mainly within the odor plume, with frequent odor contacts. With increased experience, mice shifted their strategy from this flexible, sensory-driven search behavior to a more efficient and stereotyped foraging approach that varied little in response to odor plumes. This study demonstrates that mice use prior knowledge to adaptively balance flexibility and efficiency during complex behavior guided by dynamic natural stimuli.

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Section: Discussionmentioning

confidence: 99%

Mice Develop Efficient Strategies for Foraging and Navigation Using Complex Natural Stimuli

Gire¹,

Kapoor²,

Arrighi‐Allisan³

et al. 2016

Current Biology

101

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“…One way to ameliorate this problem is to use a Mass Flow Controller (MFC) to vary the airflow through a scintillation vial containing pure odorants ( Supplementary Fig. 1im) 8,23,27,28 . The concentration of odorant in the odorized airstream depends only on the flow rate of the MFC and it is stable over time as far as there is some odorant left in the vial and the air is blown continuously through it (and sent to exhaust).…”

Section: How To Estimating the Dose-response Curve Of An Olfactory Nementioning

confidence: 99%

Controlling and measuring dynamic odorant stimuli in the laboratory

Gorur-Shandilya

Martelli

Demir

et al. 2019

Preprint

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Animals experience complex odorant stimuli that vary widely in composition, intensity and temporal properties. However, stimuli used to study olfaction in the laboratory are much simpler. This mismatch arises from the challenges in measuring and controlling them precisely and accurately. Even simple pulses can have diverse kinetics that depend on their molecular identity. Here, we introduce a model to describe how stimulus kinetics depend on the molecular identity of the odorant and the geometry of the delivery system. We describe methods to deliver dynamic odorant stimuli of several types, including broadly distributed stimuli that reproduce some of the statistics of naturalistic plumes, in a reproducible and precise manner. Finally, we introduce a method to calibrate a Photo-Ionization Detector to any odorant it can detect, using no additional components. Our approaches are affordable and flexible and can be used to advance our understanding of how olfactory neurons encode real-world odor signals.

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“…). Similarly, experimental elevation of turbulence levels caused rats to take longer to find odor sources (Bhattacharyya and Bhalla ). Other studies have shown turbulence to have no effect on avian nest survival (Conover et al.…”

Section: Introductionmentioning

confidence: 99%

“…For example, sharp-tailed grouse (Tympanuchus phasianellus) loafing locations were characterized by higher turbulence and updraft than random points (Conover and Borgo 2009), and high turbulence levels reduced the probability that hunting dogs (Canis lupus familiaris) and blue crabs (Callinectes sapidus) located odor sources (Weissburg and Zimmer-Faust 1994, Conover 2007, Jackson et al 2007. Similarly, experimental elevation of turbulence levels caused rats to take longer to find odor sources (Bhattacharyya and Bhalla 2015). Other studies have shown turbulence to have no effect on avian nest survival (Conover et al 2010, Fogarty et al 2017) and simulated prey persistence (Ruzicka and Conover 2012) or to actually increase foraging efficiency over a short distance in an aquatic environment (Ferner and Weissburg 2005).…”

Section: Introductionmentioning

confidence: 99%

Variation and drivers of airflow patterns associated with olfactory concealment and habitat selection

Fogarty

Elmore

Fuhlendorf

et al. 2018

Ecology

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Many terrestrial predators rely on olfaction to detect prey; therefore, prey should select habitat to reduce detectability of their odor cues. One way prey can potentially conceal their odor is by selecting locations with high turbulence and/or updrafts, conditions that disperse odor plumes and make odor sources difficult to locate. However, it is unclear how these conditions vary among vegetation cover types and which vegetative features drive them. We assessed variation and drivers of variables hypothesized to influence olfactory concealment (turbulence intensity and airflow slope) and experimentally evaluated whether these variables indeed influence predator detection of simulated prey. Specifically, we compared vegetation patch-scale values of turbulence intensity and airflow slope among grassland, shrubland, and forest and assessed relationships among these airflow variables and local-scale vegetative features within each vegetation type. Additionally, we experimentally investigated the importance of turbulence intensity, airflow slope, and visual concealment for predicting predator detection of scented quail eggs. In all vegetation types, we documented high variability in airflow conditions. At the patch scale, turbulence intensity was greater in shrubland and grassland than in forest, and updrafts were most common in shrubland whereas downdrafts were most common in grassland. Grassland was the only vegetation type with strong relationships among turbulence intensity and local vegetation features; both visual concealment and vegetation height were positively related to turbulence intensity. Additionally, persistence of scented quail eggs in grassland was best predicted by turbulence intensity; egg persistence increased with turbulence intensity. Our characterization of differences in olfactory variables among vegetation types provides an important step towards building a clearer understanding of olfactory landscapes. Further, our observation of both patch- and local-scale variation in olfactory variables suggests that prey can potentially select for olfactory concealment at multiple scales. We hypothesize that olfactory concealment provided by high levels of turbulence intensity is an important component of cover in grassland, and that in grassland/shrubland landscapes, prey selection of shrubland patches reduces odor detectability. Our finding of a positive relationship between turbulence intensity and visual concealment also suggests that olfactory concealment may be a previously underappreciated confounding factor in studies of habitat selection.

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Robust and Rapid Air-Borne Odor Tracking without Casting

Cited by 33 publications

References 31 publications

Mice Develop Efficient Strategies for Foraging and Navigation Using Complex Natural Stimuli

Mice Develop Efficient Strategies for Foraging and Navigation Using Complex Natural Stimuli

Controlling and measuring dynamic odorant stimuli in the laboratory

Variation and drivers of airflow patterns associated with olfactory concealment and habitat selection

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